code: def test_get_num_hops():
      class GNN(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.conv1 = GCNConv(3, 16, normalize=False)
              self.conv2 = GCNConv(16, 16, normalize=False)
              self.lin = Linear(16, 2)
  
          def forward(self, x, edge_index):
              x = torch.F.relu(self.conv1(x, edge_index))
              x = self.conv2(x, edge_index)
              return self.lin(x)
  
      assert get_num_hops(GNN()) == 2
  
file_path: pytorch_geometric/test/utils/test_subgraph.py
imports: import torch
  from torch_geometric.nn import GCNConv, Linear
  from torch_geometric.testing import withCUDA, withPackage
  from torch_geometric.utils import bipartite_subgraph, get_num_hops, index_to_mask, k_hop_subgraph, subgraph
label_desc: Use image node_id 1 for calling a global function with example usage: test_get_num_hops() and returns: self